Received: 03/04/2025 Accepted: 21/05/2025 Published: 25/06/2025 1 of 10 https://doi.org/10.52973/rcfcv-e35666 Revista Cientíﬁca, FCV-LUZ / Vol. XXXV ABSTRACT This document focuses on raw milk’s physicochemical and microbiological attributes in Napo Province, Ecuador. They explained the problem of insufﬁcient monitoring of quality control systems for raw dairy, emphasizing microbiological parameters that influenced its safety, compositional factors, and the degree of microbial activity. These parameters are necessary to improve Ecuador’s dairy industry and international competitiveness. The study’s objective focused on determining the value of the physicochemical and microbiological parameters of fat, protein, total solids, non–fat solids, SCC, and TBC to resolve the differences between regions and years. This study gathered 238 samples from collection centers and agricultural production units from Tena, Quijos, and El Chaco between 2020 and 2024. Physicochemical composition was determined using infrared spectrophotometry, while CCS and CBT were analyzed using flow cytometry. Statistical tests included the Kruskal–Wallis test, suitable for non–normal data. The results showed signiﬁcant differences between cantons and years for all analyzed parameters. The average fat content was 4.03 g·100 mL -1 , and the protein was 3.28 g·100 mL -1 . SCC and TBC levels exceeded the legal limits, reflecting challenges in hygiene and management practices. Climate, nutrition, and how herds are managed influence milk quality. There is an urgent need to implement better hygiene and management practices to optimize raw milk’s microbiological and compositional quality. Key words: Microbiological quality; total bacterial count; raw milk; physicochemical composition; regional variability RESUMEN El presente trabajo analizó la calidad ﬁsicoquímica y microbiológica de la leche cruda en la provincia de Napo, Ecuador. La investigación busca destacar la importancia de garantizar la inocuidad y el valor nutricional de la leche cruda, dado que factores como la composición y los niveles microbiológicos afectan su calidad y seguridad. Estos aspectos son críticos para el fortalecimiento del sector lácteo ecuatoriano y su competitividad en mercados internacionales. El objetivo del estudio fue evaluar parámetros ﬁsicoquímicos y microbiológicos, como grasa, proteína, sólidos totales, sólidos no grasos, conteo de células somáticas (SCC) y conteo bacteriano total (TBC), con el ﬁn de identiﬁcar variaciones por región y año. Se analizaron 238 muestras recolectadas entre 2020 y 2024 en centros de acopio y unidades productivas agropecuarias de los cantones Tena, Quijos y El Chaco. Los métodos incluyeron espectrofotometría infrarroja para composición ﬁsicoquímica y citometría de flujo para CCS y CBT. Las pruebas estadísticas incluyeron la prueba de Kruskal–Wallis, adecuado para datos no normales. Los resultados evidenciaron diferencias signiﬁcativas entre cantones y años en todos los parámetros analizados. Destaca un promedio de grasa de 4,03 g·100 mL -1 y proteína de 3,28 g·100 mL -1 . Los niveles de CCS y CBT superaron los límites normativos, esto refleja desafíos en las prácticas de higiene y manejo. Factores como el clima, la dieta y el manejo del ganado influyen en la calidad de la leche. Es urgente implementar mejores prácticas de higiene y manejo para optimizar la calidad microbiológica y composicional de la leche cruda. Palabras clave: Calidad microbiológica; conteo bacteriano total; leche cruda; composición ﬁsicoquímica; variabilidad regional Evaluation of the physicochemical and microbiological quality of raw milk in the dairy industry of Napo, Ecuador Evaluación de la calidad ﬁsicoquímica y microbiológica de la leche cruda en la industria láctea de Napo, Ecuador José Alberto de la Torres–Moreira 1 * , Milton Andrés Montalvo–Lozada 2 , Joel Oswaldo Meza–Barrezueta 3 , Verónica Gabriela Rivadeneyra–Espín 1 , Kleber Alejandro Gallegos – Guerra 4 , Kimberley Katiusca Villamarin 5 1 Fauna, Conservation and Global Health Research Group – Amazon Regional University (IKIAM). Km 7 Via Muyuna – Muyuna Parish, Tena, Ecuador. 2 Directorate of Scientiﬁc Facilities – Amazon Regional University (IKIAM). Km 7 Via Muyuna – Muyuna Parish, Tena, Ecuador. 3 Headquarters of Agricultural Health Services of Napo, Agency for Phytosanitary and Zoosanitary Regulation and Control. Tena, Ecuador. 4 Master’s student in Biotechnology Amazon Regional University (IKIAM). Km 7 Via Muyuna – Muyuna Parish. Tena, Ecuador. 5 Decentralized Autonomous Rural Government of San Francisco de Borja. Napo, Ecuador. *Corresponding author: jose.delatorres@ikiam.edu.ec

Quality of raw milk in Napo, Ecuador / de la Torres-Moreira et al. ________________________________________________________________ 2 of 10 INTRODUCTION Milk is recognized worldwide as a fundamental food due to its high protein, vitamins, minerals, and lipids content. However, in recent years, its consumption has declined in various populations due to concerns about product quality [1]. Quality is also a key demand in key markets such as Asia, where quality certiﬁcation and traceability signiﬁcantly influence consumer purchasing decisions, reflecting the demand for transparency and safety in food products [2]. Parameters such as acidity, somatic cell content, and the presence of pathogenic microorganisms deﬁne the hygienic– sanitary quality of milk. In addition, chemical residues, heavy metals, and other contaminants may enter the milk during milking, transport, or storage. For instance, De la Cueva et al. [3] reported the presence of lead, arsenic, and mercury in raw milk collected in dairy areas close to industrial hotspots in Ecuador. Some of these contaminants may pose serious health risks since they are known to be hepatotoxic, immunotoxin, or even carcinogenic [4]. Dairy producers must follow sanitary and hygienic regulations to preserve the quality and safety of milk. Stricter Veterinary and sanitary control and adequate cleaning and sanitation in the processing plants signiﬁcantly prevent microbial contamination. Monitoring somatic cell counts regularly is essential since they reflect milk’s health status and general condition [5]. In addition, detecting chemical residues and adulterants underscores the importance of rigorous testing to ensure product quality [6]. Several factors determine milk composition and can be classiﬁed as natural (intrinsic) or management–related (extrinsic). Natural factors include genetics, which varies by species and breed; the number of lactations, as production and composition change with age; and physiological status, where the stage of pregnancy or type of calving (single or double) can signiﬁcantly influence milk quality [7]. In Ecuador, at the end of 2022, 815,065 dairy cows were registered in more than 100,000 agricultural units, with a higher concentration in the Sierra region (79.5%), followed by the coast (16.3%) and the Amazon (4.2%) [8]. The Ecuadorian Technical Standard INEN 9 establishes minimum physic–chemical requirements for raw milk, such as fat content (≥3.0%), non–fat dry matter (≥8.2%), and limits for acidity, protein, and microorganisms, among other parameters. These standards aim to ensure quality that not only complies with local regulations but is also in line with international standards, thus strengthening the reputation and competitiveness of the Ecuadorian dairy industry in the global market [9]. In this context, this research aimed to evaluate the physic– chemical and microbiological quality of raw milk received by the dairy industries of Napo, Ecuador, a region with unique geographical and climatic characteristics that could influence the quality of the ﬁnal product. This study evaluated milk quality by using sanitation and composite analysis parameters. It seeks to assist in enhancing the competitiveness and food safety of the dairy sector in Ecuador. MATERIALS AND METHODS Bioethical aspects The raw milk samples analyzed were obtained by Agrocalidad during routine controls from 20 to 2024, in accordance with national food safety regulations. The company authorized their use in this research, which guarantees the traceability and anonymity of sensitive data Study area The research was conducted from 2020 to 2024 in dairy industries in the province of Napo, located in north–central Ecuador, a region characterized by diverse geography and rich biodiversity. This area is part of the Ecuadorian Amazon and covers an area of approximately 12,500 km². Its relief varies, combining the presence of tropical forests, mountains, and the influence of the Andes, creating a transitional ecosystem between the Andean foothills and the Amazon rainforest. Experimental data The data comes from the Milk Quality Laboratory of the Regulatory and Phytosanitary Control Agency (Agrocalidad) database. Between 2020 and 2024, 238 (N) analyses were carried out in the dairy industries of the province of Napo. The data corresponds to 3 cantons of the province of Napo: Tena 16.39% (n=39), Quijos 47.90% (n=114), and El Chaco 35.71% (n=85). To determine the values of fat, protein, total solids, and solids– non–fat, researchers used the infrared spectrophotometry method with the MilkoScan™ FT+ (FOSS, Denmark), and the values were expressed in (g·100 mL -1 ). To establish the somatic cell count (SCC) in raw milk, the Fossomatic™ FC (FOSS, Denmark) was used, and the total bacterial count was determined using the BactoScan™ FC+ (FOSS, Denmark), and the results were expressed in (× 1000·mL -1 ). SCC and total bacterial count (TBC) were performed using the Flow Cytometry technique, recognized by the International Dairy Federation (IDF). This technique is based on fluorescent staining of the cells, followed by chemical treatment to disperse the milk components. Subsequently, a thin sample layer is conducted through a cell flow under a fluorescent detector, which captures the light emitted by the stained cells, generating electronic pulses that are quantiﬁed to determine the number of somatic cells or bacteria present per milliliter of milk [10]. Statistical analysis The Shapiro–Wilk test showed that all the variables, except for protein, showed signiﬁcant deviations from normality (P<0.05), indicating the need to use non–parametric tests for further analysis (TABLE I). TABLE I Descriptive statistics and Shapiro–Wilk normality test for physicochemical and microbiological parameters of raw milk (n = 238) Variable N Half SD W* P (Unilateral D) Fat 238 4.04 0.58 0.73 <0.0001 Protein 238 3.28 0.15 0.97 0.0001 Total Solids 238 12.80 0.63 0.82 <0.0001 Non–Fat Solids 238 8.76 0.20 0.93 <0.0001 Somatic cell count 238 606.53 561.47 0.62 <0.0001 Total bacterial count 238 8027.54 13546.89 0.62 <0.0001 N: Number of observations, SD: Standard deviation, W*: Shapiro–Wilk test statistics for normality. D= One–tailed P–value for deviation from normality

_________________________________________________________________________________________________Revista Cientiﬁca, FCV-LUZ / Vol.XXXV 3 of 10 The Kruskal–Wallis test identiﬁed signiﬁcant differences (P<0.05) in the values of fat, protein, total solids, non–fat solids, somatic cell count (SCC), and total bacterial count (TBC), according to year and sampling location (TABLE II). a total of n= 6872 analyzed in the laboratories of the Salesian Polytechnic University from the province of Napo in the period 2009–2018, average data were obtained in the Amazon region of 3. 82 ± 0.10 %, which differs from the general average obtained in this research, in which of the total number of samples analyzed during the period 2020–2024 a general average of 4.17 was obtained, which indicates that there is an increase in the fat content of raw milk produced in livestock farms in the province of Napo. RESULTS AND DISCUSSION Physic–chemical parameters Fat Fat is a compound present in milk and is mainly composed of triglycerides, di – and mono–glycerides, fatty acids, sterols, carotenoids, vitamins (A, D, E, and K), and other trace elements [11] and is also a source of energy in the daily diet. This is the component of milk with the most signiﬁcant variability, and this variation can also be found between cows of the same breed that receive different types of feed. One factor that most affects the fat percentage in milk is based on the amount of ﬁber in the diet or the ratio of roughage to concentrate. Therefore, as ﬁber concentration increases, the proportion of fatty acids is higher than that of milk fat [12]. The results on fat content in raw milk, which averaged 4.03 g·100 mL -1 , agree with research by Fernández and Tarazona [13], suggesting that factors such as crossbreeding and diet raise the fat percentage. In El Chaco canton, fat content was exceptionally high, with an average value of 4.17 g·100 mL -1 . This may be attributed to local dietary management and supplementation practices speciﬁc to the region. Fat content varied signiﬁcantly across the years, reaching a peak in 2021 followed by a declining trend thereafter (FIG. 1). This reduction could be linked to several factors, including changes in cattle diet composition, forage quality, and thermal stress. The type of feed and season have a signiﬁcant impact on milk fat composition. For example, cows grazing on pasture during summer exhibit greater variability in fatty acid content compared to those fed total mixed rations (TMR) [14]. Moreover, forage availability and quality are seasonally adjusted to meet the nutritional needs of lactating animals, directly influencing milk quality [15]. Diets low in effective ﬁber or high in fermentable carbohydrates can alter rumen fermentation, while heat stress may reduce feed intake and impair fat synthesis. Investigating these aspects could provide valuable insights and enhance the scientiﬁc relevance of this study. According to Contero et al. [16], he states that from In the province of Napo, the areas of Quijos and El Chaco tend to have a colder climate compared to Archidona and Tena, which have warmer temperatures throughout the year; this climatic difference is mainly due to the altitude and geographical location of each area, Salazar–Cobo [17] reports that rising temperatures in the cantons of Quijos and El Chaco are associated with a decrease in the fat percentage of raw milk. In contrast, temperature increases in the cantons of Tena and Archidona do not appear to signiﬁcantly affect milk fat content. These ﬁndings are consistent with the observations of Gunn et al. [18], who attribute variations in milk fat levels to several factors, including heat stress. The Kruskal–Wallis test evaluated signiﬁcant differences in the fat variable between different years and locations (Tena, El Chaco, and Quijos). The results indicated a statistically signiﬁcant difference in the medians (H = 19.87, P=0.0108), reflecting a substantial influence of year and location on the fat values in the samples analyzed in this study. Reviewing the means and medians for each group revealed quite a difference between the groups studied, especially with the tremendous fat values in Canton El Chaco in 2021 (Table III). The elevated milk fat levels in El Chaco canton in 2021 could be explained by region–speciﬁc environmental factors and herd management strategies. The climatic conditions at that time, speciﬁcally the occurrence of droughts and heavy rains, could have impacted the physiology of the animals and, consequently, the composition of milk; this agrees with Alvear et al. [19] who note that the fat component is more signiﬁcant during some times, especially in the wet season. In this context, it is essential to consider that management practices, such as frequency and duration of milking, type of supplementary feeding, and stress level of the animals, TABLE II Summary with Kruskal–Wallis test values for each variable Variable H (K–W statistic) Df P–value Signiﬁcance Fat 19.87 2 0.0108 Yes Protein 42.01 3 <0.0001 Yes Total Solids 21.99 3 0.0049 Yes Non–Fat Solids 18.56 2 0.0173 Yes Somatic cell count 27.66 3 0.0005 Yes Total bacterial count 31.24 3 <0.0001 Yes H: Kruskal–Wallis test statistic, Df: Degrees of freedom, P–value: Probability value, Signiﬁcance: Indicates whether the test result was statistically signiﬁcant (Yes if P<0.05) FIGURE 1. Average percentage of fat in raw milk by year, from 2020 to 2024. An increase in fat content is observed up to 2021, followed by a progressive decrease in the following years. Red dots represent the annual average values, connected by a blue line to show the trend more clearly

Quality of raw milk in Napo, Ecuador / de la Torres-Moreira et al. ________________________________________________________________ 4 of 10 can also impact milk quality [20]. This interaction between environment, diet, and management has also been documented by Marini and Di Masso [21], who proposed that productive efﬁciency should be analyzed by incorporating additional variables such as longevity, reproductive behavior, and adaptability to the production system so that the implementation of management practices that reduce stress is essential to maintain animal welfare and optimize milk production [22]. Protein Milk has traditionally been considered a concentrated source of nutrients, with a high biological value protein content about its energy content [23]. Milk provides easily digestible proteins of high biological value, given that it allows for the amino acids needed to cover requirements. The protein fraction is divided into whey proteins and caseins. The serum proteins are α–lactoalbumin, β–lactoglobulin, other albumins, immunoglobulins, lactoferrin, lactoperoxidase, protease–peptone, lysozyme, and transferrin 2 [24]. A key factor in milk protein content is the type of feed and nutrition they receive, primarily through proper dietary management regarding the forage/concentrate ratio and the source of protein included [25]. Optimal nutritional management can not only improve protein levels in milk but also enhance the immune function of the animals, decreasing their susceptibility to diseases, which impacts favorably on milk production [26], another critical factor according to Jurkovich et al. [27], social dynamics is a signiﬁcant factor within herds as this can influence the stress levels of the cows, such as the genetic variability of the animal [28]. Proteins present in milk, such as casein and whey proteins, are highly valued in the food industry due to their distinctive functional properties, which are essential in various industrial processes and applications [29]; the protein content found showed an average of 3.28 g·100 mL -1 , higher than the minimum required by Ecuadorian regulations. According to Weber et al. [30], seasonal changes signiﬁcantly affect the protein content of milk; this correlates with higher temperature and humidity indexes and lower fat and protein content in milk, especially when cows are outdoors [31]. Statistical analysis showed signiﬁcant differences in protein according to year and location. The results showed a substantial difference in protein content between groups (H = 42.01, P<0.0001) (FIG. 2), indicating that the level of protein in raw milk varies signiﬁcantly depending on the site and year of sampling. These ﬁndings indicate that some local regions or the time of year may influence the protein content in raw milk obtained from various locations over different years. What can also result from genetic factors play an essential role, as heritability estimates for milk protein range from 0.284 to 0.596, suggesting the possibility that genetic selection may increase protein content without negatively affecting milk production. Also, Movedi et al. [32] have indicated that climatic events or shifts in forage growth can also strongly influence milk composition; severe weather can lower the gross protein content of forage, which is essential for compositional quality. Such adaptive approaches as implementing drought– tolerant forage species and improving pasture control can lessen these impacts and increase resilience in dairy production systems. Total solids Milk’s total solids (TS) are crucial for assessing its quality and nutritional value. TS generally includes fat, protein, lactose, and minerals, and its concentration can vary depending on several factors, including feeding practices and environmental conditions. Higher total solids content correlates with better nutritional proﬁles, including higher protein and fat content, improving dairy products’ sensory attributes [33]. Physicochemical properties, such as pH and acidity, are influenced by total solids, affecting milk’s overall quality and safety [34]. TS concentrations in raw milk vary signiﬁcantly according to species, processing methods and geographical location. These factors influence the physicochemical composition of the milk. Milk from different species (cow, goat, buffalo) has natural differences in fat, protein and lactose content, which directly affect TS levels. Similarly, processing methods such as dilution, skimming or heat treatment can alter TS concentrations. In addition, geographical variations related to climate, altitude, forage availability and feeding systems also signiﬁcantly influence the variability of this parameter. TABLE III Descriptive Statistics of Milk Fat content (g·100 mL -1 ) by Year and Canton Year Location N Mean SD Median H P 2020 Tena 39 3.84 0.36 3.87 19.87 0.0108 2021 El Chaco 12 4.32 1.29 3.96 2021 Quijos 41 4.09 0.41 4.03 2022 El Chaco 27 4.25 0.96 4.06 2022 Quijos 29 3.99 0.47 4 2023 El Chaco 31 4.11 0.29 4.15 2023 Quijos 28 4.02 0.49 4.1 2024 El Chaco 15 4.03 0.3 4.02 2024 Quijos 16 3.81 0.52 3.83 N: Number of observations, SD: Standard deviation, H: Kruskal–Wallis test statistic, P–value: Probability value FIGURE 2. Mean protein content in raw milk (g·100 mL -1 ) by year from 2020 to 2024. A Kruskal–Wallis test indicated statistically signiﬁcant diﬀerences among years (P=1.4 × 10 -6 ). Bars show annual means with standard error, and black brackets denote signiﬁcant pairwise comparisons

_________________________________________________________________________________________________Revista Cientiﬁca, FCV-LUZ / Vol.XXXV 5 of 10 A factor to consider is also the presence of microbial growth as high bacterial counts are often associated with the degradation of speciﬁc components of total solids, such as lactose, proteins and fats, due to the metabolic activity of bacteria, so that total solids levels will tend to decrease (FIG. 3), especially mesophilic bacteria (E. coli and Salmonella), can use lactose as an energy source, reducing its concentration and thus affecting the percentage of TS in raw milk [35], this correlates with Duarte et al. [36] that raw milk with high levels of TS can withstand longer storage periods without signiﬁcant degradation. Although an increase in total bacterial count (TBC) is generally expected to lead to a decrease in total solids (TS) due to the degradation of components such as lactose, protein and fat by bacterial activity, a positive correlation between TBC and TS was observed in our study. This unexpected trend could be attributed to factors such as accumulation of bacterial metabolites, evaporative water loss during handling or initial variations in milk composition. These ﬁndings suggest that, under certain conditions, higher CBT does not necessarily translate into a reduction of ST, highlighting the complexity of microbial interactions in raw milk. making seasonal changes particularly potent Kostovska et al. [38]. During warmer months, cows experience heat stress, reducing milk production and altering milk composition, including total solids and protein content. As Murphy et al. [39] noted, the number of total solids, the density, and other milk composition characteristics oscillated with the seasons. More milk solids were noted in colder seasons when cows had less heat stress. Hence, seasonality has more impact than other factors on the composition of raw milk. Non–fat solids The non–fat solids (NFS) composition of raw cow’s milk, which includes protein, lactose, and minerals [40], usually ranges between 8% and 9%. The cow’s diet signiﬁcantly influences the nutritional index of milk, and variations in dietary components affect the levels of speciﬁc nutrients, including NFS levels (without short–chain glycerol). Research indicates that different feed supplements and nutritional practices can cause marked changes in milk composition and quality. It should be emphasized that different breeds and stages of lactation can cause variations in NFS content, and older cows generally produce milk with higher levels of NFS [41]. The health status of cows due to conditions such as subclinical ketosis can alter the nutritional quality of milk, negatively modifying the composition of NFS [42], so it is essential to consider that the nutritional quality of milk can be altered using different feed supplements and dietary practices, so it is of utmost importance to closely monitor the factors that can modify it to ensure that raw milk maintains its nutritional qualities. The NFS content was 8.76g·100 mL -1 , a value that meets the quality expectations of the Ecuadorian standard NTE INEN 9:2012. The variability of NFS in raw cow’s milk from the Amazon reveals signiﬁcant variability influenced by regional and seasonal factors; this variability can be explained by various factors such as diet, cattle management, and environmental conditions since during periods of higher temperature, cows may experience heat stress, which reduces feed intake and therefore alters the concentration of speciﬁc components in the milk so that the composition of non–fat solids is higher in the winter months due to the lower presence of heat stress. This type of variability in NFS, total solids, fat, and protein (FIG. 4) has implications for the dairy industry, as it affects the quality and functionality of milk in derived products such as cheese and yogurt. The results of this study highlight the importance of considering environmental and management factors in maintaining consistency in milk quality across regions and seasons. Variability in non– fat solids content may arise from changes in feeding strategies, forage quality, lactation stage, and climatic conditions such as temperature and humidity, which affect nutrient intake and metabolic efﬁciency in dairy animals. Microbiological parameters Somatic cell count Somatic cell count (SCC) in raw milk is a critical indicator of milk quality and udder health, particularly mastitis, so high levels are generally associated with microbial contamination; they can negatively affect the chemical composition of milk [43]. International regulations control the amount of SCC in raw milk, The average total solids (12.80 g·100 mL -1 ) in this study are within the acceptable range for raw milk and comparable to those reported in other studies in the Amazon. Velez–Terranova et al. [37] suggest that seasonal and temperature variations directly affect total milk solids. Due to the amount of rainfall and the type of forage available, Amazonian conditions increase the lactose and protein content, contributing to high levels of total solids. The ﬁgures obtained from the statistical analysis of the total solid’s variable showed a stark difference in the values evaluated in the Kruskal–Wallis test (H = 21.99; P=0.0049). This denotes that the total solids content in milk differs in this study concerning the year and the collection location. In Tena, in 2020, the mean Total Solids content was 12.62 ± 0.36, whereas in other years and locations, the respective means ranged around 12.48 to 13.03 and 12.40 to 13.03 as medians. As temperature and humidity affect stress levels for the animals, there is an impact on feed intake and, ultimately, milk composition, FIGURE 3. Scatter plot showing the relationship between TBC (× 1000·mL -1 ) and TS (g·100mL -1 ) in raw milk. The red line represents the linear regression model, and the shaded area indicates the 95% conﬁdence interval

Quality of raw milk in Napo, Ecuador / de la Torres-Moreira et al. ________________________________________________________________ 6 of 10 such as the case of The European Union, which has established a maximum SCC threshold of 400,000 cells·mL -1 to ensure the safety and quality of milk [44]. The SCC values exceeded the limits established in Ecuadorian regulations. The Kruskal–Wallis test (H = 27.66, P=0.0005) reveals statistically significant differences in SCC values. It is important to emphasize that the Amazon region has very particular climatic, geographic, and cultural conditions, so dairy production management differs from other areas of Ecuador. A study conducted in the Amazon region of Peru, where SCC was evaluated in several collection centers, revealed signiﬁcant differences in the Jumbilla basin, which exhibited the lowest SCC. In contrast, other basins showed higher counts [45], suggesting different types of dairy herd management within the Amazon region, depending on the place of production. Thus, the high mean SCC in El Chaco, in contrast to Tena and Quijos (FIG. 5), could be influenced by geographic and environmental factors speciﬁc to the region, such as altitude, climate, and other ecological elements. These factors affect the health and physiology of cows. They can influence milk production and SCC, which is related to what Guliński and Kroszka [46] state: high temperatures and higher humidity, as in hot climate zones, increase the risk of mammary infections, thus increasing SCC in milk. The reduction of SCC in milk requires an integrated approach that combines good management practices with the control of environmental factors. Put hygiene protocols for milking and udder dipping; these practices should constitute Good Agricultural Practices (GAP) to prevent mastitis [47]. Moreover, the effect of heat stress on herd health, milk quality, and other factors must be considered. Ventilation systems can enhance welfare while, at the same time, reducing CSS through the control of environmental bacterial load [48]. Total bacterial count Total Bacterial Count (TBC) is one of the basic parameters of quality raw milk and cows’ health, especially when checking for mastitis. Elevated levels of CBT indicate that farm hygienic practices are low, which can affect an increase in CCS count and ﬁnally impact milk production and proﬁtability [49]. In regions with a tropical climate like the Amazon, TBC control becomes complicated because of environmental conditions that support the growth of pathogens and impede proper milk preservation. The mean TBC in raw milk (8027.54 × 1000) was much higher than the cutoff set by the regulations and was similar to Arauco– Villar et al. [50] ﬁndings of high bacterial burdens in the raw milk of Peruvian Andean herds, which was primarily due to poor hygienic milking and product handling practices. The P values relative to the Kruskal–Wallis (H) analysis of variance at the various sites are signiﬁcant (P<0.05), validating that the differences in CBT between locations and years are indeed statistically signiﬁcant. The most pronounced difference between 2020 and 2024 (FIG. 6) could be related to changes in health policies, management practices, or even climatic events that affected milk production conditions. Poor cleaning protocols for transport equipment can raise the bacterial load, as seen in an email where transported samples had higher counts than farm samples [51]. Poor storage practices can also influence the proliferation of spoilage microorganisms on dairy products, thus affecting shelf life and safety [52]. Also, tropical regions like the Amazon have difﬁculties because of high humidity combined with high temperatures that aid the growth of microorganisms. FIGURE 4. Average values (g·100 mL -1 ) of fat, protein, non–fat solids, and total solids in raw milk from the cantons of El Chaco, Quijos, and Tena. Bars represent mean values by component and canton FIGURE 5. Heatmap showing raw milk’s average somatic cell count (SCC, log10 scale) by canton and year. Darker red tones represent higher values FIGURE 6. Dot plot shows the distribution of TBC values by year. Each blue dot represents an individual sample, while red dots indicate yearly meaning

_________________________________________________________________________________________________Revista Cientiﬁca, FCV-LUZ / Vol.XXXV 7 of 10 The variability in mean values of TBC between Cantons, such as El Chaco ( 6814.84 × 1000 mL) and Quijos,(10633.84 × 1000 mL) over the years could suggest that certain areas face more signiﬁcant difﬁculties in implementing effective hygiene and management controls, suggesting poor barn hygiene and inadequate cleaning of milking equipment contribute to elevated levels of bacteria in milk [53]; speciﬁc management practices, such as the use of appropriate drying materials and mastitis control programs, can substantially improve milk quality by reducing bacterial contamination counts. Seasonal comparison of milk quality parameters To determine whether precipitation intensity influences milk quality in the Amazonian region, samples were grouped into ‘more rainy’ (November to June) and ‘less rainy’ (July to October) seasons based on INAMHI criteria for the Amazon region. TABLE IV summarizes the results of the Mann–Whitney U test comparing milk parameters between both periods. CONCLUSIONS The high levels of TBC and SCC reflect the urgent need to improve hygiene practices during milking, storage, and transport in Napo province; training and adopting technologies are essential to reducing these values. The physicochemical composition of milk (fat, protein, and total solids) varies significantly according to altitude, environmental conditions, and management practices in each canton, highlighting the importance of optimizing feeding and reducing heat stress in cattle. ACKNOWLEDGMENTS The authors would like to thank the Jefatura de Servicios de Sanidad Agropecuaria de Napo (Agrocalidad) for allowing the publication of this article using information from the UPS database. Conflict of interests The authors declare no conflict of interest regarding the publication of this manuscript. BIBLIOGRAPHIC REFERENCES [1] Castellini G, Barello S, Bosio A. Milk quality conceptualization: A systematic review of consumers, farmers and processing experts views. Foods [Internet]. 2023; 12(17):3215. doi: https://doi.org/prcz [2] Abbas H, Ullah H, Gong X, Jiang M, Faiz N, Zhao L. Sustainable market environment and consumer conﬁdence in food safety in China after COVID-19: urban consumer perspectives. Econ. Finance Lett. [Internet]. 2022; 9(2):139-156. doi: https://doi. org/prc2 [3] De la Cueva F, Naranjo A, Puga–Torres B, Aragón E. Presencia de metales pesados en leche cruda bovina de Machachi, Ecuador. La Granja [Internet]. 2021; 33(1):21-30. doi: https:// doi.org/gm29 [4] Puga B, Aragón E, Ron L, Álvarez V, Bonilla S, Guzmán A, Lara D, De La Torre D. Milk quality parameters of raw milk in Ecuador between 2010 and 2020: A systematic literature review and meta–analysis. Foods [Internet]. 2022; 11(21):3351. doi: https://doi.org/prc3 [5] Chabanenko DV. Ensuring milk quality and safety in industrial production. Sci. Messin. LNU Vet. Med. Biotech. Series: Vet. Sci. [Internet]. 2024; 26(114):144-153. doi: https://doi.org/prc4 [6] Kotelevych V, Huralska S, Olishevskyi V. Veterinary and sanitary assessment of raw milk for improvement of technology to increase quality and safety in private JSC “Podillya” food company. Sci. Prog. Innov. [Internet]. 2024; 27(1):118-125. doi: https://doi.org/prc5 [7] Tirﬁe FW. A Review of Genetic and Non–Genetic Parameter Estimates for Milk Composition of Cattle. Anim. Vet. Sci. [Internet]. 2023; 11(3):64-70. doi: https://doi.org/prc6 The seasonal comparison of raw milk parameters between the rainy and dry periods in Napo revealed that total bacterial count (TBC) was significantly higher during the rainy season (P=0.0156), while fat, protein, total solids, non–fat solids, and somatic cell count did not show signiﬁcant differences (P>0.05) (TABLE IV). This result aligns with ﬁndings from other tropical regions, where increased rainfall and humidity contribute to greater microbial proliferation during milking, storage, and transportation processes [54]. Elevated TBC values during the rainy season may be linked to environmental contamination, inadequate sanitation during collection, and slower cooling times in high–moisture conditions [55]. Although no signiﬁcant variation was observed in the physicochemical composition, the slight reduction in fat content during the dry season could reflect changes in pasture availability or animal hydration status, consistent with observations in similar Amazonian studies [56]. The lack of signiﬁcant variation in somatic cell count suggests that udder health is not substantially affected by rainfall intensity in this region, likely due to consistent management practices across the year [57]. These findings underscore the importance of reinforcing hygienic handling and cold chain protocols during high–rainfall months to mitigate microbial risks, particularly in tropical dairy systems [58]. TABLE IV Comparison of raw milk quality parameters between rainy and dry seasons in Napo, Ecuador (2020–2024) Variable Mean Rainy Season Mean Dry Season P–value Sig. Fat 4.05 ± 0.53 4.02 ± 0.64 0.057 No Protein 3.28 ± 0.15 3.27 ± 0.15 0.7083 No Total Solids 12.82 ± 0.61 12.78 ± 0.67 0.1366 No Non–fat solids 8.76 ± 0.22 8.77 ± 0.22 0.9367 No Somatic cell count 623.46 ± 514.48 582.36 ± 624.45 0.3686 No Total bacterial count 9062.19 ± 14486.80 6549.48 ± 11955.84 0.0156 Yes P–value: Probability value, Sig.: Signiﬁcance, indicates whether the test result was statistically signiﬁcant (Yes if P<0.05)

Quality of raw milk in Napo, Ecuador / de la Torres-Moreira et al. ________________________________________________________________ 8 of 10 [8] Instituto Nacional de Estadística y Censos (INEC). Encuesta de superﬁcie y producción agropecuaria continua – 2023 [Internet]. Quito (Ecuador): Instituto Nacional de Estadística y Censos. 2024 [cited Feb 23, 2025]. Available in: https:// goo.su/LvK6o5c [9] Mora–Córdova DE, Lituma–Loja AA, González–Illescas ML. Las certiﬁcaciones como estrategia para la competitividad de las empresas exportadoras. INNOVA Res. J. [Internet]. 2020; 5(2):113–132. doi: https://doi.org/prc7 [10] Remón–Díaz D, González–Reyes D, Martínez–Vasallo A. Evaluación de la calidad higiénico–sanitaria de la leche cruda por métodos de flujo citométrico. Rev. Salud Anim. [Internet]. 2019 [cited Feb 15, 2025]; 41(1):1-8. Available in: https:// goo.su/gztYyzo [11] Quispe–Alanya D. Calidad e inocuidad de la leche cruda producida en el centro poblado de Chanquil–Los Morochucos, acopiada y comercializada en Ayacucho [degree thesis on the Internet]. Perú: Universidad Nacional San Cristóbal de Huamanga; 2024 [cited Feb 15, 2025]. 193 p. Available in: https://goo.su/zkoU0Yz [12] González–Escobar YJ. Influencia de la edad de los animales en indicadores productivos, reproductivos y de calidad de la leche [Dissertation on the Internet]. Cuba: Universidad de Matanzas; 2022 [cited Feb 21, 2025]. 151 p. Available in: https://goo.su/5Kplqa [13] Fernández J, Tarazona G. Factores que influyen en la composición de la leche en el sector el Retorno, Parroquia Sabanilla, Cantón Zamora, Provincia de Zamora Chinchipe– Ecuador. Rev. Politéc. [Internet]. 2015 [cited Feb 20, 2025]; 36(2):34. Available in: https://goo.su/73vEyT1 [14] Kowalska M, Mitrosz P, Żbikowska A, Molik A. Influence of animal nutrition on milk quality with special reference to the fatty acid composition of milk fat. Acta Pol. Pharm. [Internet] 2024; 81(1):123-134. doi: https://doi.org/prdc [15] Topnikova EV, Zabolotin GYU, Danilova ES, Dunaev AV. Influence of diets, lactating animal breeds and seasons of the year on the fatty acid composition of cow milk. IOP Conf. Ser. Earth Environ. Sci. [Internet]. 2022; 1052(1):012042. doi: https://doi.org/prdf [16] Contero R, Requelme N, Cachipuendo C, Acurio D. Calidad de la leche cruda y sistema de pago por calidad en el Ecuador. La Granja [Internet]. 2021; 33(1):31-43. doi: https://doi.org/prdg [17] Salazar–Cobo JA. Influencia de factores meteorológicos en la calidad de la leche cruda de vaca en Ecuador [degree thesis on the Internet]. Ecuador: Escuela Politécnica Nacional; 2022 [cited Jan 28, 2025]. 147 p. Available in: https://goo. su/CMcgmsN [18] Gunn KM, Holly MA, Veith TL, Buda AR, Prasad R, Rotz CA, Soder KJ, Stoner AM. Projected heat stress challenges and abatement opportunities for US milk production. Plos One [Internet]. 2019; 14(3):e0214665. doi: https://doi.org/gnwqdp [19] Alvear DC, Guerrero JD, Bonifaz NF, Noriega PF. Calidad composicional y concentración de ácidos grasos omega-3 (alfa–linolénico) y omega-6 (linoleico) presentes en leche bovina de tres regiones naturales del Ecuador. Rev. Fac. Med. Vet. Zootec. [Internet]. 2021; 68(2):150-169. doi: https:// doi.org/prdh [20] Mioč B, Antunović Z, Siric I, Novoselec J, Kasap A, Klir– Salavardic Z, Ramljak J, Drzaic V. The influence of different stress factors on the production and quality of sheep milk. Mljekarstvo. [Internet]. 2024; 74(3):169-184. doi: https:// doi.org/prdj [21] Marini PR, Di Masso RJ. Evaluación histórica de indicadores productivos en vacas lecheras en sistemas a pastoreo. La Granja [Internet]. 2018; 28(2):103-115. doi: https://doi.org/prdk [22] Koenneker K, Schulze M, Pieper L, Jung M, Schmicke M, Beyer F. Comparative assessment of the stress response of cattle to common dairy management practices. Animals [Internet]. 2023; 13(13):2115. doi: https://doi.org/prdm [23] Sánchez MA, Murray RS, Montero J, Marchini M, Iglesias R, Saad G. Importancia de la leche y sus potenciales efectos en la salud humana. Actualiz. Nutr. [Internet]. 2020 [cited Feb 24, 2025]; 21(2):50-64. Available in: https://goo.su/yRZr9r4 [24] Beaudry KM, Devries MC. Nutritional strategies to combat type 2 diabetes in aging adults: The importance of protein. Front. Nutr. [Internet]. 2019; 6:138. doi: https://doi.org/prdn [25] Olika CD. Review on effect of nutrition on milk composition and yield of dairy cows. Eur. J. Sci. Innov. Technol. [Internet]. 2021 [cited Feb 27, 2025]; 1(2):24-31. Available in: https:// goo.su/BcdcDuw [26] Musa HH, Mwacharo JM, Adam SY, Cai D, Ahmed AA. Climate change, nutrigenomics, immune function and diseases and production in dairy cattle: a comprehensive review. Appl. Vet. Res. [Internet]. 2023; 2(2):2023010. doi: https://doi. org/prdp [27] Jurkovich V, Hejel P, Kovács L. A review of the effects of stress on dairy cattle behaviour. Animals [Internet]. 2024; 14(14):2038. doi: https://doi.org/prdq [28] Hossein–Zadeh NG. Evidence of additive genetic variation for major milk proteins in dairy cows: A meta–analysis. J. Anim. Breed. Genet. [Internet]. 2024; 141(4):379-389. doi: https:// doi.org/prdr [29] Cortez JXM, Patiño DAP, Paredes JFM, Castillo VEV. Lactosuero: Materia prima para la elaboración de productos con valor agregado. Bol. Inf. CEI. [Internet]. 2022 [cited Feb 10 2025]; 9(1):103-106. Available in: https://goo.su/9rOnQ [30] Weber CT, Schneider CLC, Busanello M, Calgaro JLB, Fioresi J, Gehrke CR, Haygert–Velho IMP. Season effects on the composition of milk produced by a Holstein herd managed under semi–conﬁnement followed by compost bedded dairy barn management.Semin. Cienc. Agrar. [Internet]. 2020; 41(5):1667-1678. doi: https://doi.org/prds [31] Hill DL, Wall E. Dairy cattle in a temperate climate: the effects of weather on milk yield and composition depend on management. Animal [Internet]. 2015; 9(1):138-149. doi: https://doi.org/f6sq4q

_________________________________________________________________________________________________Revista Cientiﬁca, FCV-LUZ / Vol.XXXV 9 of 10 [32] Movedi E, Paleari L, Argenti G, Vesely FM, Staglianò N, Parrini S, Confalonieri R. The application of a plant community model to evaluate adaptation strategies for alleviating climate change impacts grassland productivity, biodiversity and forage quality. Ecol. Model. [Internet]. 2024; 488:110596. doi: https://doi.org/g8ns92 [33] Vekariya Y, Deep A, Kathiriya M, Tellabati R. Impact of Raw Milk Quality on Dairy Products & Payment Systems. Asian Res. J. Agric. [Internet]. 2024; 17(2):116-122. doi: https:// doi.org/prgz [34] Kazeminia M, Mahmoudi R, Mousavi S, Mehrabi A. Raw cow milk quality: physicochemical, microbiological, and seasonal variation. J. Microbiol. Biotechnol. Food Sci. [Internet]. 2023; 13(3):e10078. doi: https://doi.org/prg2 [35] Williams EN, Van Doren JM, Leonard CL, Datta AR. Prevalence of Listeria monocytogenes, Salmonella spp., Shiga toxin– producing Escherichia coli , and Campylobacter spp. in raw milk in the United States between 2000 and 2019: A systematic review and meta–analysis. J. Food Prot. [Internet]. 2023; 86(2):100014. doi: https://doi.org/prg3 [36] Duarte RV, Casal S, da Silva JAL, Gomes A, Delgadillo I, Saraiva JA. Nutritional, physicochemical, and endogenous enzyme assessment of raw milk preserved under hyperbaric storage at variable room temperature. ACS Food Sci. Technol. [Internet]. 2022; 2(6):961-974.doi: https://doi.org/prg4 [37] Vélez–Terranova M, Campos–Gaona R, Salamanca–Carreño A, Velasco–Daza RA, Arenas–Rodríguez BA, Chaparro– Ortegón JS. Environmental factors that affect the sanitary and nutritional variability of raw milk in dual purpose livestock systems of Colombian Orinoquia. Animals [Internet]. 2023; 13(8):1385. doi: https://doi.org/prg5 [38] Kostovska R, Horan B, Drouin G, Tobin JT, O’Callaghan TF, Kelly AL, Gómez–Mascaraque LG. Effects of multispecies pasture diet and cow breed on milk composition and quality in a seasonal spring–calving dairy production system. J. Dairy Sci. [Internet]. 2024; 107(12):10256-10267. doi: https://doi.org/prg6 [39] Murphy S, Martin N, Barbano D, Wiedmann M. Influence of raw milk quality on processed dairy products: How do raw milk quality test results relate to product quality and yield?. J. Dairy Sci. [Internet]. 2016; 99(12):10128-10149. doi: https://doi.org/f9b7c3 [40] Azhar S, Jamil W, Ali AH, Iftikhar B, Orakzai M, Afaq Y, Arshad A, Azhar A, Ali W. Analysis of physicochemical and nutritional parameters of raw milk from commercial dairy farms – Implications of adulteration for public health. J. Med. Sci. [Internet]. 2024; 32(1):65–70. doi: https://doi.org/prg7 [41] Tirﬁe FW. A Review of Genetic and Non–Genetic Parameter Estimates for Milk Composition of Cattle. Anim. Vet. Sci. [Internet]. 2023; 11(3):64-70. doi: https://doi.org/prc6 [42] Zhao Y, Zhao H, Li L, Tan J, Wang Y, Liu M, Jiang L. Multi– omics analysis reveals that the metabolite proﬁle of raw milk is associated with dairy cows health status. Food Chem. [Internet]. 2023; 428:136813. doi: https://doi.org/prg8 [43] Mehany ESN, El–Shafaie MA, Fahim KM, Sallam SS. Relationship between somatic cell count and different microbial and chemical quality parameters of bulk tank milk. Adv. Anim. Vet. Sci. [Internet]. 2021; 9(10):1660-1668. doi: https://doi.org/prg9 [44] Şteţca G, Mocuţa N, Chindriş V, Coldea TE. Monitoring milk somatic cell counts. Food Sci. Technol. [Internet]. 2014; 71(2):221-222. doi: https://doi.org/prhb [45] Frías H, Murga L, Portocarrero–Villegas SM, Arista–Ruiz MA, Pinedo LS, Escobedo HD, Maraví C, Milla Pino ME, Culqui Vilca J, Alvarado Chuqui W, Segura Portocarrero GT, Saucedo– Uriarte JA, Bardales W. Physicochemical and sanitary parameters of raw cow’s milk intended for consumption in the Amazonas region, Peru. Preprints. [Internet]. 2023; 2023081107. doi: https://doi.org/prhc [46] Gulinski P, Kroszka MK. The influence of selected environmental factors on the number of somatic cells in cistern and alveolar milk of Polish Holstein–Friesian cows. Animals [Internet]. 2024; 14(15):2219. doi: https://doi.org/prhf [47] de Araujo–Lopes CM, Praxedes CIS, de Sousa–Oliveira JM, Muruci LNM. Influência das boas práticas agropecuárias na contagem padrão em placas (CPP) e na contagem de células somáticas (CCS) no leite cru. Braz. J. Dev. [Internet]. 2022; 8(3):21519–21536. doi: https://doi.org/prhg [48] Quintana ÁR, Seseña S, Garzón A, Arias R. Factors affecting levels of airborne bacteria in dairy farms: A review. Animals [Internet]. 2020; 10(3):526. doi: https://doi.org/gm4mhk [49] Markusson H. Total bacterial count as an attribute for raw milk quality [Internet]. Sweden: Swedish University of Agricultural Sciences, SLU. 2021 [cited Feb 15, 2025]; 28 p. Available in: https://goo.su/WpZ6IT [50] Arauco–Villar F, Guzmán–Estremadoyro L, Pantoja–Esquivel R, Mayorga–Sánchez N, Unchupaico–Payano I, Huamán de la Cruz A. Evaluación de la calidad ﬁsicoquímica, microbiana e higiénica de la leche de vaca producida por rebaños en los Andes peruanos. La Granja [Internet]. 2025; 41(1):127-139. doi: https://doi.org/prhk [51] Paludetti LF, Kelly AL, O’Brien B, Jordan K, Gleeson D. Microbiological quality of milk from farms to milk powder manufacture: an industrial case study. J. Dairy Res. [Internet]. 2019; 86(2):242-247. doi: https://doi.org/prhm [52] Kumar S, Kumar S, Lodh J, Mishra D. Microbiological quality and safety in the dairy industry. Microb. Path. Zoon. Milk Borne Dis. [Internet]. 2024; 407–419. doi: https://doi.org/prhn [53] Ahmed ZA, Kasim MH, Tegegne B, Salah HM. Assessment of hygiene practices and bacteriological quality of raw cow milk of selected dairy farm in Dessie, Ethiopia. Am. J. Aquac. Anim. Sci. [Internet]. 2022; 1(1):27–37. doi: https://doi.org/ prhp [54] Li N, Wang Y, You C, Ren J, Chen W, Zheng H, Liu Z. Variation in Raw Milk Microbiota Throughout 12 Months and the Impact of Weather Conditions. Sci. Rep. [Internet]. 2018; 8(1):2371. doi: https://doi.org/gcv7mv

Quality of raw milk in Napo, Ecuador / de la Torres-Moreira et al. ________________________________________________________________ 10 of 10 [55] Queiroz RLL, Coelho KO, Passos AA, Valadão L, Ribeiro RV. Contagem bacteriana total do leite cru refrigerado em função do período do ano. Pubvet. [Internet]. 2019; 13(4):152. doi: https://doi.org/prhq [56] Guzman Estremadoyro LJ, Huaman Salome P, Ninahuanca Carhuas J, Ore Guzman S, Aquino Tacza A, Flores Guillen MA, García–Olarte E. Effects of Different Seasons on Milk Quality: A Study on Two Cattle Breeds in Rainy and Drought Contexts. World Vet. J. [Internet]. 2024; 14(2):213–219. doi: https:// doi.org/prhr [57] Sadeghi–Seﬁdmazgi A, Rayatdoost–Baghal F. Effects of herd management practices on somatic cell counts in an arid climate. Rev. Bras. Zootec. [Internet]. 2014; 43(9):499-504 doi: https://doi.org/pszp [58] Pramod D, Saxena N. An overview of on–farm hygienic milk production. Int. J. Innov. Res. Eng. Manag. [Internet]. 2022; 9(1):369–372. doi: https://doi.org/prht